2012
DOI: 10.1590/s0103-90162012000300001
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Abstract: Fertilizer application at variable rates requires dense sampling to determine the resulting field spatial variability. Defining management zones is a technique that facilitates the variable-rate application of agricultural inputs. The apparent electrical conductivity of the soil is an important factor in explaining the variability of soil physical-chemical properties. Thus, the objective of this study was to define management zones for coffee (Coffea Arabica L.) production fields based on spatial variability o… Show more

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Cited by 36 publications
(36 citation statements)
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“…Data on the two harvests did not reveal any gain by implementing the CVI index, due to the similar performances of FPI and MPE. However, specialized literature (Li, Shi, Wu, Li, & Li, 2008;Valente et al, 2012) reports instances in which the above failed to occur and that CVI would provide a less subjective decision on the best interpolation or on the number of management areas.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Data on the two harvests did not reveal any gain by implementing the CVI index, due to the similar performances of FPI and MPE. However, specialized literature (Li, Shi, Wu, Li, & Li, 2008;Valente et al, 2012) reports instances in which the above failed to occur and that CVI would provide a less subjective decision on the best interpolation or on the number of management areas.…”
Section: Resultsmentioning
confidence: 99%
“…Among the techniques in MZ generation, one may mention clustering algorithms, such as K-Means and Fuzzy C-Means (Iliadis, Vangeloudh, & Spartalis, 2010;Arno Martinez-Casasnovas, Ribes-Dasi, & Rosell, 2011;Valente, Queiroz, Pinto, Santos, & Santos, 2012;Li, Shi, Wu, Li, & Li, 2013), which provide good results (Mingoti & Lima, 2006;Jipkate & Gohokar, 2012).…”
Section: Introductionmentioning
confidence: 99%
“…The IDE was lower in this study probably because were obtained lower density of samples than obtained by MOLIN & CASTRO (2008), who collected one sample per second. With semivariance model (Table 1) the spatial variability raster maps was generated using kriging interpolation by Krig-me software (VALENTE et al, 2012). The spatial correlations, using global bivariate Moran's index (I), between the CE20 and soil properties raster maps were calculated (Table 2).…”
Section: Resultsmentioning
confidence: 99%
“…A post-processed differential correction was performed using GNSS Solutions® software provided by the GPS device manufacturer. Raster maps were obtained by kriging using the Krig-me software (VALENTE et al, 2012).…”
Section: Methodsmentioning
confidence: 99%
“…Although any attribute may be related to crop yield, for DOERGE (2000), the ideal attribute is the correlation of predictable spatial information sources with yield. Clustering techniques for MZ generation include algorithms such as K-Means and Fuzzy C-Means (ILIADIS et al, 2010;VALENTE et al, 2012 andLI et al, 2013), which offer good results (VITHARANAet al, 2008;MORARI et al, 2009;MORAL et al, 2010;RODRIGUES JUNIOR et al, 2011;DAVATGAR et al, 2012;KWEON, 2012;BANSOD & PANDEY, 2013), which permit the automatic division of the studied field. In this approach, different data sources that are related to crop development factors can be used to generate MZs.…”
Section: Introductionmentioning
confidence: 99%